Marker Combos Promising for Predicting Cognitive Decline

But results fall short of what's needed for a clinically useful screen.

Action Points

Note that these studies were published as abstracts and presented at a conference. These data and conclusions should be considered to be preliminary until published in a peer-reviewed journal.

A combination of biomarkers for Alzheimer's disease prediction showed good sensitivity and specificity for predicting later onset of cognitive impairment in healthy middle-aged people.

Note that one study suggests that the marker combinations were feasible and promising for Alzheimer's disease prediction, and could become useful tools in the short term for enriching clinical trial samples for testing new therapies.

WASHINGTON -- A combination of well-studied biomarkers for Alzheimer's disease prediction showed good sensitivity and specificity for predicting later onset of cognitive impairment in healthy middle-aged people, according to results from a long-running prospective study reported here.

Based on data from the so-called BIOCARD study that began in 1995, a model incorporating six markers yielded specificity of 75% and sensitivity of 80% for predicting which cognitively normal individuals would progress to mild cognitive impairment (MCI) or clinical Alzheimer's disease within five years, said Marilyn Albert, PhD, of Johns Hopkins University in Baltimore.

But the results indicated that most positive results obtained from the model were false, given that less than 20% of the sample actually converted to MCI or Alzheimer's disease during follow-up.

Albert, who presented the findings at the Alzheimer's Association International Conference, said the main message from the study was that marker combinations were feasible and promising for Alzheimer's disease prediction. Also, they could become useful tools in the short term for enriching clinical trial samples for testing new therapies.

At a press conference prior to her formal presentation, she said BIOCARD provided a good laboratory in which to develop predictive models for cognitive decline.

BIOCARD has actually had two phases, Albert explained. The first ran from 1995 to 2005, with 349 initial participants with a mean age of 57 at enrollment. Participants underwent a battery of cognitive tests at baseline along with MRI brain scans and cerebrospinal fluid sampling. Just under 60% of the group was female, and 75% had a family history of dementia. Mean educational level was 17 years of schooling.

Four years after that phase concluded, researchers at Hopkins obtained funding to re-enroll the original participants for additional follow-up. That phase began in 2009 and is still continuing, Albert said. Almost 90% of the initial sample agreed to rejoin the study.

During the now almost 20 years of follow-up -- the mean was 10 years -- about 60 participants received diagnoses of MCI or Alzheimer's disease, she said.

Earlier analyses of the BIOCARD data had shown that individual markers were clearly associated with increased or decreased risk of cognitive decline, but that was through Cox regression analyses that produced group-based hazard ratios. Such analyses are less useful at the individual patient level for prediction, she observed.

Out of the many markers tracked during the study, which included multiple MRI parameters, proteins in cerebrospinal fluid (CSF) and blood, and neurocognitive tests, the researchers identified six as most suitable to be included in a combination model:

Phosphorylated tau in CSF

APOE genotype

Right-side entorhinal cortical thickness

Right-side hippocampal volume (age-corrected)

Digit symbol test score

Paired associate test score

Including adjustments for age and education, the resulting model yielded a receiver-operating characteristic curve with an area of 0.85, Albert said.

However, the specificity of 75% meant that, in a clinical setting, it would not be reliable for predicting future decline to MCI/dementia status. Of the roughly 300 participants continuing in the second study phase, 60 had progressed to a clinical diagnosis. But with a 25% false-positive rate for the model, that means approximately 75 participants were falsely predicted to convert. Thus, the positive predictive value was necessarily less than 50%.

Albert said the model had not been re-tested in an independent patient sample. She also said the group hoped to improve the model by adding more markers of various kinds, including possibly the beta-amyloid plaque burden as measured with PET tracers as well as cognitive tests targeting specific functional domains.

A similar combination approach is also being taken in a Canadian study called PREVENT-AD with a two-fold aim: testing naproxen for slowing progression of so-called preclinical Alzheimer's disease and to develop a robust biomarker-based endpoint for this and other drug trials.

"We assume no single marker will suffice," said John Breitner, MD, MPH, of McGill University in Montreal, who gave a brief overview of the study at the same session where Albert spoke.

Analogous to the effort Albert is leading, the Canadian group is developing an "Alzheimer Progression Score" based on different types of markers, some of which have previously been demonstrated to show detectable changes over periods as short as one year.

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